Development of a GEANT4-Based Monte Carlo algorithm for polarized nuclear imaging simulations integrated into GATE.

Background: Polarized Nuclear Imaging (PNI) is a novel gamma imaging approach that encodes spatial information by using polarized radioactive nuclei and manipulating them with magnetic fields, gradients, and RF pulses. The resulting anisotropic photon emission yields direct k-space encoding, removing the need for collimators.

Purpose: The work will focus on developing the first, high-performance Monte Carlo-based algorithm for PNI, fully integrated into the GATE framework. Using Monte Carlo simulations, there is an expectation of a strong push in research concerning PNI and a better understanding and use of this new imaging technique.

Methods: An algorithm based on Geant4 was implemented and coupled with GATE in the form of a new type of source. This extension allows users to define a PNI source, configure its parameters, and use GATE's basic functionalities to perform simulation studies in PNI. The source of GATE-based PNI generates photons in directions according to the PNI-encoded method, which maps spatial information into the spin orientations of polarized radioactive nuclei.

Results: The tool exhibited extremely small average relative errors (∼0.0000018 %) when replicating theoretical angular distributions of gamma emissions from oriented nuclei, and a 3.57 % difference from theory in extracting k-space data using the detector-based PNI method. A complex PNI source also yielded results consistent with experimental data.

Conclusions: This GATE-based PNI simulation toolkit offers an efficient, user-friendly, and accurate method for investigating PNI, paving the way for advanced research and system optimization.